1. Field of the Invention
This invention relates to an online line-scan imaging system capable of simultaneous acquisition of both hyperspectral/multispectral Vis/NIR reflectance and fluorescence images using a single image acquisition device such as for example a Charge Coupled Device (CCD) and to a method of using the system to simultaneously detect and/or inspect (multitasks) a multiple combination of physical, chemical, and biological attributes of products, such as contamination and defects, especially agricultural commodities.
2. Description of the Related Art
The safe production of foods to minimize foodborne illnesses is a concern for both the general public and the entire food industry (Mead et al., Emerging Infectious Diseases, Volume 5, 607-625, 1999). Contamination of food products by animal fecal matter is recognized as a major culprit for pathogenic E. coli O157:H7 (Armstrong et al., Epidemiology Rev., Volume 18, 29-51, 1996; Cody et al., Ann. Internal Medicine, Volume 130, 202-209, 1999). Fruits with defects, such as cuts, lesions, and rots that are known to provide favorable ecological niches for bacterial growth are also a safety concern (Mercier and Wilson, Biol. Control, Volume 4, 138-144, 994; Burnett et al., Appl. Environ. Microbiol., Volume 66, 4679-4687, 2000). Opto-electronic imaging techniques as rapid nondestructive sensing tools have been incorporated into agricultural production inspection. Various sensing techniques including the use of X-rays, RGB color, visible/near-infrared (Vis/NIR) reflectance, and fluorescence have been investigated for potential use in online applications (Chen et al., J. Food Process Eng., Volume 21, 351-367 1998; Chen and Tao, Applied Optics, Volume 40 (8), 1195-2000, 2001; Kim et al., 2000(a), J. of Food Engineering, Volume 71 (1), 85-91, 2005; Chao et al., Applied Engineering in Agriculture, Volume 15 (4), 363-369, 1999, Applied Eng. In Agriculture, Volume 20 (5), 683-690, 2004; Mehl et al., J. Food Engin., Volume 61 (1), 67-81, 2004; Liu et al., Applied Spectroscopy, Volume 59 (1), 78-85, 2005; Throop et al., Postharvest Biology and Technology, Volume 36 (3), 281-290, 2005; Yang et al., Trans. ASABE, Volume 49 (1), 245-257, 2006). The most prevalent is reflectance in Vis/NIR portions of the spectrum, used in either monochromatic or multispectral regimes. Optical imaging or machine vision techniques hold great potential for rapid quality and safety inspection of agricultural commodities. In particular, the efficacy of fluorescence imaging for postharvest food safety inspection for fecal contamination has been demonstrated using fruits artificially contaminated with a range of diluted animal feces (Kim et al., Trans. ASAE, Volume 45 (6), 2039-2047, 2002b, Applied Optics, Volume 42 (19), 3927-3934, 2003a, 2005 (supra); Lefcourt et al, Applied Optics, Volume 42 (19), 3935-3943, 2003; Vargas et al., J. of Food Science, Volume 70 (8), E471-E476, 2005).
In the apple processing industry, for example, an online-based machine vision system is typically dedicated to performing a specific sorting task. Current commercial systems address sorting by size, shape and color. The apple industry is in need of sorting methods for apples with defects such as fungal growth, cuts, lesions, bruises, rots, and insect damage. In order to achieve rapid sorting and meet inspection objectives for various quality and safety attributes, multiple machine vision systems may be needed.